Document image processor, method for extracting document title, and method for imparting document tag information

ABSTRACT

A document image processing device and method for extracting a title region and a mark attached by the user from a document image to use them as document tag information. A region with a region average character size larger then a predetermine extraction judging value is extracted as a title region by title region extracting means. As a result, title regions can be extracted from one document image. A mark that the user makes on an input image is extracted by mark extracting means, and characteristic value of the mark is found by calculating means. Document tag information to be imparted to the input image is selected from reference tag information according to the characteristic value and the attribute value of the reference tag information imparting means. Thus, document tag information is automatically imparted to a document image.

TECHNICAL FIELD

This invention relates to a document image processor and a documentimage processing method for storing and managing document images asimage data, more specifically relates to apparatus and a method forextracting title regions and marks attached by a user from a documentimage to use them as document tag information.

BACKGROUND OF ART

Together with an improvement of capability of data storage, documentimage processors rapidly become popular in which a paper document readfrom a scanner and etc. is stored and managed as a document image thatis image data of the document.

It is arranged in such document image processor that each document imageis registered corresponding to character strings that are document taginformation like a keyword or a title, in order to search a desireddocument image from plural document images stored in a data storage.

FIG. 19 shows the document tag information conceptually. As shown in thedrawing, the document tag information, such as “Confidential” 191,“A-company” 192, “Year 1999” 193 and “New car” 194, for example, acts asa keyword for a document image 190. Provided that a plurality ofdocument tag information is attached to each document image in this way,it is possible to search a desired document image by limiting thoseplural document tag information.

In a conventional way, a user has inputted by hand those document taginformation at storing of the document image. When the user input thedocument tag information, however, if the number of documents increases,the workload becomes large. Accordingly, such inputting operation isquite impractical. So in recent years the other apparatus has appearedthat is able to recognize characters on the document image, handle arecognized character string as document tag information, and then attachthe document tag information to the document image without assistance ofhand labor.

For instance, Japanese laid-open publication No. 8-147313 discloses amethod of using a mark sheet. In the method, first, a user checks off acheck box of document tag information to be attached to a documentimage, the document tag information described on the mark sheet in aspecific form. The mark sheet is read by a document image processorbefore the paper document is read, whereby the document tag informationto be attached can be specified from the nominees of document taginformation registered in advance. The method does not require a use ofan input device such as a keyboard or a pointing device, and it ispossible to attach the document tag information automatically to thedocument image to be registered.

Incidentally, it is very important for an effective searching ofdocument images to give appropriate document tag information to thedocument images. Specifically, a general searching method is to specifydocument tag information corresponding to a desired document image froma list of plural document tag information displayed on a screen. And inorder to specify such document tag information quickly, respectivedocument tag information should express the contents of the documentdirectly.

The Japanese Laid-open Publication No. 8-202859 discloses another methodwherein a region including a title-character string (which is called a“title region” hereafter) is extracted from a document image, and thecharacters in the image of the title region is recognized, and then arecognized title-character string is made to document tag information.Since the title-character string represents the contents of the documentdirectly, an image data processor adopting the title-region extractingmethod can quickly specify the document tag information corresponding tothe desired document image.

The above method of extracting the title region, which is disclosed inJapanese laid-open publication No. 8-202859, is based on the aspect thatthe title characters are in the largest size among all of charactersincluded in the document image. After dividing the document image intoplural regions (a region to which consecutive character rectangles arecombined), and calculating an average of character size in therespective regions, a region in which the average of character size isthe maximum is extracted as a title region. Accordingly, it is naturalthat the title-region extracting method extracts only one title regionfor a document image.

However, if there are plural documents with the similar contents, thedocuments always have the similar titles each other. Therefore, theconventional title-region extracting method had a problem that, whenthere are plural documents with similar contents, it is impossible toquickly specify the document tag information corresponding to thedesired document image.

In order to avoid the above problem there is a method without attachingsimilar titles to documents at preparing paper documents. However, it isundesirable to request a user to do the preparatory operation.

On the other hand, the method in Japanese laid-open publication No.8-147313, which uses a mark sheet, has a very troublesome work that itis necessary to define the form of the mark sheet describing all itemsof the document tag information, and to define the reading method of themark sheet, when a document image processor is configured as thesoftware. In addition, in case of adding and registering nominees of newdocument tag information later on, the items of document tag informationare changed. Thereby, it is necessary to reconstruct the form of themark sheet and the reading method.

In addition, in case of using the mark sheet, since the user always usesthe same sheet to check off the check box, it is hard for a user tovisually confirm which document tag information is attached to thedocument image, and it causes inputting mistakes frequently.

The invention is proposed taking the above problems into consideration,and has an object to provide the document image processor for extractingtitle regions and marks attached to a document image by the user from adocument image to use them as document tag information, and to providethe method for extracting document titles, and the method for impartingdocument tag information.

DISCLOSURE OF THE INVENTION

The invention adopts the following means in order to achieve theobjects.

A document image processor, as shown in FIG. 1, comprising regiondividing means 103 for dividing a document image into a plurality ofregions, and title-region extracting means 104 for calculating a firstaverage that is an average of character size in each region divided bythe region dividing means 103, and extracting title regions from all theregions according to the first averages, the document image processoradopts the following means.

After calculating a second average equivalent to an average height ofcharacters included in all the regions, the title-region extractingmeans 104 compares the first average and an extracting criterion that isthe second average multiplied by an extracting parameter, and thenextracts, as a title region, regions with the first average larger thanthe extracting criterion. Accordingly, if the region has the firstaverage larger than the extracting criterion, the region is extracted asa title region. Therefore, it is possible to extract a plurality oftitle regions from a document image.

In addition, the title-region extracting means 104 may calculateextracting criteria on a plurality of levels by using extract parameterson a plurality of levels. Thereby, the extracting judgment can beperformed based on respective extracting criteria on a plurality oflevels, so that it is possible to extract not only title regions butalso subtitle regions (a region including a subtitle-character stringcomposed of characters in a little smaller size than the titlecharacter).

Furthermore, the title-region extracting means 104 may determine theextracting parameters on a plurality of levels based on a value found bydividing the maximum value of the first average by the second average.If the extracting parameter is calculated based on the maximum value ofthe first average without being limited to a fixed value, it is possibleto obtain the extracting criteria more accurately.

And since the trimmed mean method for excluding characters larger than aspecific proportion of the maximum character size and characters smallerthan the specific proportion of the minimum character size is used tocalculate the second average and the first average, it is possible toimprove the accuracy of the extracting further more.

Moreover, the image of characters included in the extracted title regioncan be converted to a title-character string of a character code stringby character recognizing means 105. Correcting means 112 corrects thetitle-character string; thereby a user can change the title of thedocument image freely.

Secondary, in the document image processing for preparing and storingdocument images by reading a paper document, reference tag informationstorage means 1215 is provided as shown in FIG. 12 for storing referencetag information (a nominee of document tag information) together with anattribute value of the reference tag information in advance.

Next, mark extracting means 1205 is provided for extracting a specificmark attached to a paper document by a user. The mark indicates ageneral mark imparted in order for a user to identify the paperdocument, such as a stamp, a seal, an illustration, a signature ofspecific handwriting, and etc.

Calculating means 120A is provided in order to calculate acharacteristics value representing the characteristics of the markaccording to the variance of pixels composing the extracted mark.

Document tag information imparting means 1208 is provided for comparingthe attribute value and the characteristics value, selecting thereference tag information with the highest degree of similarity, andthen imparting the selected reference tag information to the documentimage.

According to the above steps, it is possible to automatically impart thedocument tag information to the document image based on the mark thatthe user uses at the routine work of document filing Therefore, theinvention makes it easy to operate the document management at theoffice.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a schematic functional block diagram of a document imageprocessor in the first embodiment of this invention.

FIG. 2 shows a flowchart of the title-region extracting process in thefirst embodiment of the invention.

FIG. 3 shows a flowchart of the title-region extracting process in thesecond embodiment of the invention.

FIG. 4 shows a flowchart of the title-region extracting process in thethird embodiment of the invention.

FIG. 5 shows an explanatory diagram of the registration informationmanagement table in the first embodiment.

FIG. 6 shows an explanatory diagram of the registration informationmanagement table in the second embodiment.

FIG. 7 shows an explanatory diagram of the labeling process.

FIG. 8 shows an explanatory diagram of the region dividing process.

FIG. 9 shows a diagram indicating the correlation among the height, thewidth, and the area of the character rectangle.

FIG. 10 shows a diagram representing the contents displayed on a screenat the searching in the first embodiment.

FIG. 11 shows a diagram representing the contents displayed on a screenat the searching in the second embodiment.

FIG. 12 shows a schematic functional block diagram of a document imageprocessor in the fifth and sixth embodiments of the invention.

FIG. 13 shows an explanatory diagram of the registration imagemanagement table in the fifth and the sixth embodiments of theinvention.

FIG. 14 shows an explanatory diagram of the mark management table in thefifth embodiment of the invention.

FIG. 15 shows an explanatory diagram of the reference tag informationmanagement table.

FIG. 16 shows an explanatory diagram for the extracted mark image.

FIG. 17 shows an explanatory diagram the registration image managementtable in the sixth embodiment of the invention.

FIG. 18 shows an explanatory diagram of the mark management table in thesixth embodiment of the invention.

FIG. 19 shows an explanatory diagram expressing the conception of thedocument tag information.

BEST MODE FOR CARRYING OUT THE INVENTION Embodiment 1

The embodiments of the invention are explained hereafter referring tothe drawings. The embodiments 1, 2, 3 and 4 are explaining about adocument image data processor for extracting plural titles from a paperdocument.

FIG. 1 shows a schematic functional block diagram of a document imageprocessor to which the present invention is applied. The configurationof the processor will be explained together with the process of thedocument image registration.

First, an image inputting means 101 like a scanner, for example,performs the photoelectric conversion of a paper document, and then adocument image 108 a that is multi-valued image data is obtained. Afteran image processing means 111 a performs an appropriate processing forthe storing (the compressing, for example), the document image isregistered in a document image area Aa of a storage means 108. Needlessto say, it may be configured that the document image processor is notprovided with the image processing means 111 a, but registers themulti-valued image data in the document image area Aa without change.

The document image inputted to the image processing means 111 a from theimage inputting means 101 is also inputted to an image processing means111 b. Here, the document image is converted to binary image data, andthen stored into an image memory 107. Referring to the document imagestored in the image memory 107, a character rectangle creating means 102performs the following labeling process. The labeling is a processingfor imparting the same label value (identification information) as anotable black pixel (which is called a “target pixel” hereafter) toother black pixels of pixels contiguous to 8 directions of the targetpixel, that is, the top side, the upper right side, the right side, thelower right side, the down side, the lower left side, the left side, andthe upper left side, of the target pixel. That is to say, as shown inFIG. 7, where 8 pixels, W1, W2, W3, W4, W6, W7, W8 and W9 are contiguousto the target pixel W5, the character rectangle creating means 102 givesthe label value same as that of the target pixel W5 to the black pixelsW2, W3 and W8. According to such labeling, the same label value can begiven per black-pixel-connected component in the document image (percontinuous black pixels).

Next, the character rectangle creating means 102 prepares a characterrectangle by cutting off the black-pixel-connected component attachedwith the same label value, and then transfers the character rectangle toregion dividing means 103. Here, the “character rectangle” means acircumscribed rectangle of a black-pixel-connected component. However,there is a case where a character is not always configured by oneblack-pixel-connected component. In consideration of this, it can bearranged that a section of the black pixel in the document image isexpanded before the labeling. Specifically, the processing is forconverting the 8 pixels contiguous to the target pixel to black pixels.The processing is repeated by appropriate times (generally twice ortriple), thereby the section of black pixel is enlarged, and accordinglyit is possible to combine respective black-pixel-connected components,which form a character and are apart from each other within thecharacter, into one unit. If the labeling is performed after theabove-mentioned processing, it is possible to prepare the characterrectangle per character precisely.

When the character rectangle creating means 102 completes theprocessing, the region dividing means 103 detects areas adjacent torespective character rectangles, and then divides the document image toregions by combining the character rectangles contiguous with eachother. For instance, the region dividing means 103, upon receipt of thecharacter rectangles C1 to C12 as shown in FIG. 8, combines thecharacter rectangles C1 to C4, C5 to C9, and C10 to C12 respectively,and then divides the document image into regions E1, E2 and E3.According to thus region dividing, the document image can be dividedinto regions per character string. In order to judge whether thecharacter rectangles are contiguous with each other or not, or whetherthere is an interlinear blank between the character rectangles or not,proper threshold values of a character gap and an interlinear space maybe used to the judgment.

As a result of the above processing, it is possible to obtain theinformation of the size of all the characters in the document image(which will be described later), the number of the divided regions, andthe number of the character rectangles in each region. It is arranged inthe invention that the serial number starting from 1 be given to eachdivided region and also be given to each character rectangle included inthe region respectively. Hereinafter, the number of character rectanglesin the n-th region is represented by NumChar_(n), and the size of them-th character in the n-th region is represented by SizeChar_(n,m).

Incidentally, as shown in FIG. 9, if the characters are the same fontand the same typography point, widths W1 to W4 and areas A1 to A4 forthe character rectangle depend on the character itself and fluctuatesharply, conversely heights H1 to H4 of the character rectanglefluctuates a little. Therefore, the invention may adopt as the charactersize “the height of character rectangle”, on which the point of acharacter font is reflected comparatively correctly.

Here, a title-region extracting means 104 extracts only specific regionsas a title region from all regions divided as above. The title-regionextracting is explained hereinafter according to a flowchart shown inFIG. 2.

Fist, the title-region extracting means 104 calculates a first averageper region (FIG. 2, Step 1). The first average is an average of size ofcharacters included in a region. The first average in the n-th region,SizeReg_(n), is found by dividing the sum (SizeChar_(n,m)) of all thesizes of the characters included in the region by the number(NumChar_(n)) of characters in the region. This correlation isrepresented by the following equation.SizeReg _(n) =ΣSizeChar _(n,m) /NumChar _(n)  [Equation 1]

Next, according to the first average SizeReg_(n) and the number ofcharacters in the region NumChar_(n), a second average, SizeALL, whichis an average of character size in the document image, is calculated bythe following equation (FIG. 2, Step 2).SizeALL=Σ(SizeReg _(n) ×NumChar _(n))/ΣnumChar _(n)  [Equation 2]

The method of calculating the first average SizeReg_(n) and the secondaverage SizeAll is not restricted to the above method. For example, itis possible to adopt the trimmed mean method (a method of calculatingthe average after discarding a specific proportion, for example, 10% ofdata, from the minimum value and the maximum value), which will beexplained later.

Here, according to the judgment whether or not the following equationfor the extracting judgment is established, the title-region extractingmeans 104 performs the extracting judgment of the title region.SizeReg _(n) >=SizeALL×α  [Equation 3]

That is to say, after comparing a value found by multiplying thecalculated second average SizeALL by an extracting parameter α (anextracting criterion) and the first average SizeReg_(m), only the regionwhere the equation of the extracting judgment is established isextracted as a title region (FIG. 2, Step 3 to 4 to 5). The extractingparameter α should be a constant that is larger than 1.0, and it ispreferable to 1.2, for example.

When the extracting judgment is performed for all the regions byrepeating the above steps (FIG. 2, “NO” in Step 3), the title-regionextracting is completed. Then respective title-region images 108 bextracted as above are registered in a title area Ab of the storagemeans 108.

Next, character recognizing means 105 cuts the title-region imagesextracted from the document image off, performs the characterrecognizing for each title-region image, and then obtainstitle-character strings that are a character code string. Thosetitle-character strings thus obtained are transferred to display controlmeans 110 via correcting means 112, and are shown to a user bydisplaying them in a list view on a screen that is not shown (see FIG.10(I)).

The user confirms each title-region image and title-character stringthus displayed, and if he wants to register one of the title-characterstrings in the same state as shown on the screen, he instructs aninstruction inputting means 109 to register it. Then, thetitle-character string is transferred from the character recognizingmeans 105 to document registering means 106.

On the other hand, if the user wants to correct or change any of thetitle-character strings, he double-clicks a title-character string thusdisplayed by means of a pointing device of the instruction inputtingmeans 109. According to the double-clicking, the correcting means 112instructs the display control means 110 to blink the title-characterstring on the screen and display the cursor within the character string.Then the user, operating the keyboard of the instruction inputting means109, inputs a corrected character string in the correcting means 112,whereby the character string following to the cursor can be replacedwith the corrected character string. By inputting the correctedcharacter string to the character recognizing means 105 from thecorrecting means 112, the title-character string is corrected. Likewise,when the user instructs to perform the registration by the instructioninputting means 109, the corrected title-character string is transferredfrom the character recognizing means 105 to the document registeringmeans 106.

However, in case where the confirmation and the correcting are notprogrammed, the contents recognized by the character recognizing means105 is to be transferred to the document registering means 106 as it is,without displaying it on the screen.

After receiving the title-character string, the document registeringmeans 106 registers the registration information composed of the storagepointer of the document image 108 a and the title-region image 108 b inthe storage means 108, the title-character string, and the position andsize of the title region in the document image into a registrationinformation management table 108 c formed in the table area Ac on thestorage means 108 (see FIG. 5). Here, the storage pointer of thedocument image 108 a can be obtained from the document image area Aa onthe storage means 108, the storage pointer of the title image 8 b can beobtained from the title area Ab on the storage means 108, and theposition and the size of the title region can be obtained from thecharacter recognizing means 105.

After the registration information management table 108 c is prepared asabove, in case where the instruction of the searching of the documentimage is inputted by the instruction inputting means 109 such as akeyboard and a pointing device, the display control means 110 displaysin a list view the title-region images and the title-character stringstored as above on the screen (FIG. 10(I)).

When the user selects a desired title (a title-region image or atile-character string) from the listed titles on the screen by means ofthe instruction inputting means 109, the display control means 110displays on the screen the document image corresponding to the selectedtitle. At this time, as shown in FIG. 10(II), it is preferable that thetitle region in the document image is indicated clearly bycircumscribing it with a rectangular frame F. The rectangular frame Fcan be prepared according to the position and the size of the titleregion registered in the registration information management table 108c.

In addition to the above method of selecting either one title from thelist displayed on the screen, it can use a method that, when the userinputs specific document tag information from the instruction inputtingmeans 109, if the title corresponding to the specific document taginformation has been registered in the registration informationmanagement table 108 c, the corresponding document image may bedisplayed on the screen.

In accordance with this embodiment described as above, since it isarranged that regions with the first average larger than the extractingcriterion be extracted as a title region, it is possible to extractplural title regions from a document image. Therefore, even if there aremany document images having similar contents, it is possible to quicklyspecify the document tag information (the title) corresponding to thedesired document image.

The above explanation does not refer to the steps for a case where thereis no region in which the extracting judgment equation is established atthe title-region extracting. However, in this case, a message that notitle region can be extracted is displayed on the screen and the inputof a character string to be the document tag information is requested tothe user. The user inputs the character string in response to therequest, and then the inputted character string can be used as thetitle-character string for the document image.

Embodiment 2

It is arranged in the embodiment 1 that, if the regions have the firstaverage larger than the extracting criterion, those regions be extractedas a title region without discrimination. By this method, it isimpossible to display the titles by discriminating between the charactersizes, that is to say, the processing is such as, where a titlecharacter string in a little small character size is handled as asubtitle, the subtitle character string is not listed up but only thetitle character string is displayed.

In the embodiment of the invention, the above-mentioned problem issettled by calculating plural extracting criteria by using plural levelsof extracting parameters, and then extracting the title regions bycorrelating the title regions with the level attributes (informationindicating the level of the extracting). The configuration will beexplained hereafter regarding to the points different from that of theembodiment 1.

The title-region extracting means 104, which calculates the firstaverage SizeReg_(n) and the second average SizeAll according to the samesteps as in the embodiment 1, performs the extracting judgment of plurallevels according to the result whether the following equation for theextracting judgment on the plural levels is established or not.SizeReg _(n) >=SizeALL×α_(p)  [Equation 4]

α_(p) in the above equation is a extracting parameter on the p-th level(the level p), and the value of α_(p) should be predetermined so as tosatisfy the condition of the equation 5. When the extracting judgment isperformed on 5 levels, it is preferable that each parameter should bedetermined as approximate α1=1.5, α2=1.3, α3=1.2, α4=1.15, and α5=1.1.1.0<α_(p)< . . . <α3<α2<α1  [Equation 5]

The flowchart shown in FIG. 3 is explained here. The title-regionextracting means 104 performs the extracting judgment on every level inthe order from the level 1 (FIG. 3, Steps 14 to 15 to 14). When theextracting judgment equation is not established on any level, the regionis not extracted as the title region but the title-region extractingmeans 104 performs the extracting judgment for the next region (FIG. 3,Steps 14 to 13 to 14 to 15). On the other hand, when the extractingjudgment equation is established on either one level, the region isextracted as the title region on that level (which is correlated withthe level attribute) and then the extracting judgment is performed forthe next region (FIG. 3, Steps 15 to 16 to 13 to 14 to 15).

After the extracting judgment is performed for every region by repeatingthe above steps (FIG. 3, “NO” at Step 13), the title region extractingis completed.

Besides, when there is no region where the extracting judgment equationis established, the character string inputted by a user is used as thetitle-character string, which is the same as the embodiment 1. The levelattribute of this title-character string is set as the level 1 and thenumber of total levels is set as 1.

In addition, the extracted title-character string can be changed orcorrected, which is the same as the embodiment 1.

FIG. 6 is an explanatory diagram of the registration informationmanagement table 1 in this embodiment. It is arranged that the “levelattribute” field 601 and the “number of levels” field 602 be added tothe configuration described in the embodiment 1. And when there is anyregion extracted on the level 1 of the 5 levels of the extractingjudgments, the document registering means 106 registers “5” on the“number of levels” field 602 and “1” on the “level attribute” field 601respectively.

FIG. 11 is a diagram showing the contents displayed on the screen at thesearching in this embodiment. It is arranged that each range of thelevel attribute of the titles to be displayed in a list view on theupper portion can be selected by the instruction inputting means 109.And the display control means 110 displays on the screen in a list viewthe titles having the level attribute within the range selected asabove, referring to the “level attribute” field 601 and the “number oflevels” field 602 in the registration information management table 108c.

In accordance with this embodiment described above, it is arranged thatthe extracting criteria of plural levels be calculated by using theextracting parameters of plural levels and the title regions beextracted corresponding to each level attribute. Therefore it ispossible to perform various processing by discriminating between thefirst averages, for example, for displaying in a list view thetitle-character strings only, without displaying in a list view thesubtitle-character strings.

Embodiment 3

It is arranged in the embodiment 2 that the extracting parameters ofplural levels be predetermined (as a fixed value), however, it ispreferable that the extracting parameters should be determined accordingto respective characteristics of the inputted document images. It isarranged in this embodiment that the extracting parameters of plurallevels be determined based on a value found by dividing the maximumvalue of the first averages by the second average (see FIG. 4, Step 23).The configuration will be explained regarding only the point differentfrom that of the embodiment 2.

After calculating the first average SizeReg_(n) and the second averageSizeAll according to the same steps as in the embodiment 2, thetitle-region extracting means 104 calculates first the value α1 that isthe maximum value of the first averages, max{SizeReg_(n)}, divided bythe second average SizeAll, according to the following equation.α1=max{SizeReg _(n) }/SizeAll  [Equation 6]

Next, by using the following equation, the title-region extracting means104 determines the extracting parameters α_(p) on each level inaccordance with thus calculated al and the number of total levels P(P>=1) for the extracting judgment.α_(p)=α1−(p−1)×(α1−1)/P  [Equation 7]

For instance, where the extracting judgment is performed on 5 levelswhen α1 is 1.5, the extracting parameters α1 to α5 on each level arecalculated as follows.α1=1.5−(1−1)×(1.5−1)/5=1.5α2=1.5−(2−1)×(1.5−1)/5=1.4α3=1.5−(3−1)×(1.5−1)/5=1.3α4=1.5−(4−1)×(1.5−1)/5=1.2α5=1.5−(5−1)×(1.5−1)/5=1.1  [Equation 8]

According to the equation 7, the extracting parameter α_(p) on eachlevel can be determined so as to be equidistance between thus calculatedα1 and 1.0.

The steps after the above steps is the same as that of the embodiment 2excluding the extracting judgment by using the extracting parametersdetermined as described above, and those steps are not explained here.

In the above method, however, where there is no title region in thedocument image, α1 becomes a value near to 1.0, for example, 1.03, and atext region is extracted as a title region by mistake. In order to avoidsuch trouble, this invention is arranged so as not to use the extractingparameter under a specific value, for example, 1.5.

In addition, when the difference between extracting parameters on eachlevel is not more than a specific value, 0.03, for example, theextracting judgment cannot be performed precisely. Accordingly, it isarranged that the set value of the extracting parameter be corrected sothat the difference between the extract parameters on each level may besaid specific value (0.03). Practically, in the above case, values,which are found by subtracting 0.03 from the respective extractingparameters from α1 to α5 in order, are determined as the extractingparameter.

As a result of the above, there is a possibility that the number oftotal levels P reduces. In this case, the actual number of levels (whichis the reduced number of levels subtracted from the number of totallevels P) is registered as the number of total levels P on the “numberof total levels” field 602 in the registration information managementtable 108 c.

In this embodiment as described above, it is arranged that theextracting parameters should not be fixed, but determined based on thecharacteristics of the inputted document image. Therefore it is possibleto perform the extract determination precisely.

Embodiment 4

In each of the above-mentioned embodiments, the characters of the titleregion in the relatively large size are also taken into the calculationof the second average, and the small characters such as a comma, aperiod, and punctuation are also taken into that calculation. Therebythe calculation result has an inclination to bring down the accuracy ofthe title extracting. Therefore it is arranged in this embodiment thatthe second average be calculated based on the total characters in thedocument image excluding the characters of which sizes are larger than aspecific ratio (90%, for example) and characters of which sizes aresmaller than a specific ratio (10%, for example). That is to say, thetrimmed mean method is adopted here. In addition, even when the firstaverage is calculated, the same trouble occurs, too. Therefore, it ispossible to apply the trimmed mean method to the calculation of thefirst average.

As a result, it is possible to calculate the second average and thefirst average regarding the characters excluding a period, a comma andpunctuation, so that the calculated averages becomes more precisevalues.

Here, in each of the aforementioned embodiments, the second average iscalculated from the first average. But, when this method is applied tothe trimmed mean method, characters in large size and characters insmall size are excluded from each title region. For this reason, all thecharacters included in the title regions should not be excluded for thecalculation of the second average. Therefore, it is arranged in thisembodiment that the second average be calculated for the totalcharacters in the document image again.

However, even in case of using the trimmed mean method, it is needlessto say that either one of the specific value in the embodiment 1 and thelevel values in the embodiments 2 and 3 can be used as the extractingparameter.

The each explanation of the above embodiments does not refer to thenumber of the original image documents, but the number of the originalsis not limited particularly. That is to say, even if there is only onesheet or plural sheets, it is possible to obtain the same effect as faras the same extracting parameter is used in each page. In particular, itis possible in the embodiments 2 and 3 to extract accurately the titleregions and the sub-title regions from one document composed of pluralpages, such as a data of the thesis, by using the same extractingparameter to plural pages.

According to the above explanations, the height of the characterrectangle is adopted as the character size, but the width or the area ofthe character rectangle can be adopted as the character size.

As illustrated in FIG. 1, since the image processing means 111 a and 111b are provided at the stage before the storage means 108 and the imagememory 107 respectively, it is possible to use a binary image as adocument image for the title extracting as well as use a compressedimage or a multi-valued image as a document image data to be stored inthe document image area Aa of the storage means 108. Thereby, it ispossible to display in various ways the document images obtained as aresult of the searching based on the title regions thus extracted, likedisplaying in color.

Embodiment 5

Here in the embodiments 5 and 6 is explained about the document imageprocessor that recognizes the marks attached on, the paper document asthe document tag information.

First, marks such as a title or a keyword are given to any pagecomposing the paper document by a user. Here the mark indicates ageneral mark given by a user so as to identify the paper document, likea stamp, a seal, an illustration, a signature of specific handwriting,and so on.

When the document image processor in the invention stores the papercomposed of a plurality of pages, it is necessary to judge which page ofthe paper document the marks are attached to. At this time, though thereis a method for detecting the marks after the searching all over thetotal pages of the paper document, there is a problem in the method thatit takes much time for the detecting.

The method to solve said problem is as follows; for instance, thedocument image processor is configured so as to detect a mark on thefirst page only, in advance.

In this embodiment of the invention, the marked pages (which is called“document tag information appointing page” hereafter) 21 and 24 can bedistinguished from others by describing the specific 2-dimensional codeimage 26 on the specific position of the lower right, as shown in FIG.13( b).

FIG. 12 shows a block diagram of the document image processor in theembodiment 5 of the invention. The steps of the processing by thedocument image processor will be explained hereafter.

First, the image inputting means 1201 converts the paper document to anelectronic data by using an photoelectric converter such as a scanner, adigital integrated apparatus, and so on, and then inputs the document asthe document images. Here, as shown in FIG. 13, the document taginformation attached to the document tag information appointing page 21,“Confidential”, “A-company”, and “Year '99”, should be given to theinputted images 22 and 23, and the document tag information attached tothe document tag information appointing page 24, “Confidential” and“B-company”, should be given to the inputted image 25. And the imageinputting means 1201 is inputted the document tag information appointingpage 21, the input image 22, the input image 23, the document taginformation appointing page 24 and the input image 25, in those order.

The inputted document image is stored in the image memory 1202temporarily, for which the image data compressing means 1203 performedthe data compressing. After that, said data is stored in the imagestorage area 1211 of the storage means 1210. At this time, in order toidentify each document image thus stored, an image ID is given to thedocument image respectively. The image ID is registered in the “imageID” field 121 of the registration image management table 1212 shown inFIG. 13( a). In addition, the pointer information pointing to the imagedata stored in the image storage area 1211 of the storage means 1210 isregistered in the “pointer to image data” field 122 of the registrationimage management table 1212.

On the other hand, the document image stored in the image memory 1202 isalso sent to the mark extracting means 1205 after the binarization bythe binarization means 1204. The mark extracting means 1205 judgeswhether the specific two-dimensional code image is at the predeterminedposition of the lower right of the image or not, and determines whetherthe inputted document image is the document tag information appointingpage or not respectively.

At this time, if the document image is determined as the document taginformation appointing page, “1” is registered on the “document taginformation appointing page flag” field 123 of the registration imagemanagement table 1212, if not, “0” is registered on it. The flag isapplied to the identification that the document image is the documenttag information appointing page attached with the marks only and doesnot contains the content as the text of the paper document. Forinstance, after the document tag information are given to the documentimage according to the other-mentioned method, the document imagecorresponding to the document tag information appointing page can bedeleted according to the flag. Thereby it is possible to avoid a wasteof the memory resources.

A mark management group No. is given to the entire document imagesinputted between the first document tag information appointing page andthe next one. In addition, the mark management group No. is registeredon the “mark management group No.” field 125 of the registration imagemanagement table 1212. Here, it means that the document image to whichthe same document tag information is given is imparted the same markmanagement group No.

The next explanation refers to the processing that the mark extractingmeans 1205 extracts the marks from the document image determined as thedocument tag information appointing page according to the aboveprocessing.

First, as described in the embodiment 1 it labels the entire regionsexcluding the regions attached with the two-dimensional code among thedocument tag information appointing pages. Among a plurality of theblack pixels contiguous components obtained by the labeling, thecomponents that have the distance from each other smaller than thespecific threshold value are combined to one region. The regions thusobtained are corresponding to the regions of marks 41 to 43respectively, as shown in FIG. 16. Those regions are extracted, andthereby each mark image can be obtained.

The number of marks extracted from each document tag informationappointing page is registered on the “number of marks” field 124 of theregistration image management table 1212.

In addition, in order to manage the information of the extracted markimages, each mark image is attached with a mark ID, and then registeredon the “mark ID” field 131 of the mark management table 1213 as shown inFIG. 14. The mark management group No. of the document tag informationappointing page attached with the mark is registered on the “markmanagement group No.” field 132 of the mark management table 1213.Regarding each of the mark images extracted from the document taginformation appointing page, the information about the position and thesize (the width and the height) of the mark image within the documenttag information appointing page are registered on the “position” field134 and the “size” field 135 of the mark management table 1213respectively.

In this embodiment, the document images inputted between the firstdocument tag information appointing page and the next one is attachedwith the same mark management group No., and managed as a series ofdocument images attendant on the first document tag informationappointing page. It can be considered as another management method thatonly the specific document image inputted after the document taginformation appointing page is given the mark management group No. andthe other document images are not given any number. This method can beapplied when a user wants to give the table of contents to the specificdocument image.

Next, the characteristics value calculating means 1206 of thecalculating means 120A calculates the numerical value representing thecharacteristics of the mark image extracted by the mark extracting means1205. The invention applies the characteristics value of the MomentInvariants of the well-known prior arts to this numerical value. Thefollowing explanation is made regarding the Moment Invariants in brief.

When the coordinates of a pixel is represented by (i, j) and the valueof the pixel is represented by I(i, j), I is a function that satisfiesI=1 for the black pixel meanwhile satisfies I=0 for the white pixel. Them_(pq) defined by the Equation 9 is called the (p+q)-dimensional moment.m _(pq)=Σ_(i)Σ_(j) i ^(p) j ^(q) I(i, j) p,q=0, 1, 2, . . .   [Equation9]

In case of applying the above m_(pq), the center of gravity (x, y) ofthe two-dimensional image is represented by the Equation 10.x=m ₁₀ /m ₀₀y=m ₀₁ /m ₀₀  [Equation 10]

μ_(pq) defined by the Equation 11 according to the center of gravitythus calculated is called the center moment.μ_(pq)=Σ_(i)Σ_(j)(i−x)^(p)(j−y)^(q) I(i,j)  [Equation 11]

The numerical values M1 to M6 calculated as follows by the Equation 12according to the above center moment are defined as the characteristicsvalue of the corresponding two-dimensional image (or on the MomentInvariants).M1=μ₂₀+μ₀₂M2=(μ₂₀−μ₀₂)²+4μ₁₁ ²M3=(μ₃₀−3μ₁₂)²+(3μ₂₁−μ₀₃)²M4=(μ₃₀+μ₁₂)²+(μ₂₁+μ₀₃)²M5=(μ₃₀−3μ₁₂)(μ₃₀+μ₁₂)[(μ₃₀+μ₁₂)²−3(μ₂₁+μ₀₃)²]+(3μ₂₁−μ₀₃)(μ₂₁+μ₀₃)[3(μ₃₀+μ₁₂)²−(μ₂₁+μ₀₃)²]M6=(μ₂₀−μ₀₂)[(μ₃₀+μ₁₂)²−(μ₂₁+μ₀₃)²]+4μ₁₁(μ₃₀+μ₁₂)(μ₂₁+μ₀₃)  [Equation12]

Since those characteristics values are unchangeable even in case of therotation or the translation of the two-dimensional image, those becomethe effective value for characterizing the mark like the embodiment ofthe invention when a user gives a specific mark to a sheet by hand.

The characteristics value calculated by the characteristics valuecalculating means 1206 is given to the similarity calculating means 1207of the calculating means 120A, where the similarity between thesecharacteristics value and the attribute value of respective referencetag information is calculated. In order to explain this method, thefollowing is the explanation about the management method of thereference tag information and the calculating method of attribute valueof the respective reference tag information.

The reference tag information is the data correlated with the mark thata user will use in the future (which is called the “reference mark”hereafter), specifically, and the nominee of the document taginformation like the character string playing a role as a keyword forthe inputted image. The reference tag information is registered on the“reference tag information” field 141 of the reference tag informationmanagement table 1214 as shown in FIG. 15( a). The image data of thereference mark is stored in the reference tag information storage means1215. The pointer to this image data is registered on the “pointer toreference mark image” field 142 of the reference tag informationmanagement table 1214. The characteristics value calculating means 1206calculates six characteristics values of those reference marks on theMoment Invariants, which are registered on the “attribute value (M1 toM6)” field of the reference tag information management table 1214. Thatis to say, those characteristics values are the attribute values of therespective reference marks.

The distance between the attribute value of the reference mark thuscalculated and the respective characteristics value on the MomentInvariants of the mark image extracted from the inputted image iscalculated by the Equation 13.L=(m1−M1)²+(m2−M2)²+(m3−M3)²+(m4−M4)²+(m5−M5)²+(m6−M6)²  [Equation 13]

The above M1 to M6 represent the attribute value of the reference mark,while the above m1 to m6 represent the characteristics value of theextracted mark image. It expresses that the smaller the distance Lcalculated by the above equation, the higher the similarity of theextracted marked image and the reference tag information is.

The document tag information imparting means 1208 specifies a referencemark of which similarity is the maximum value, and selects the referencetag information of the reference mark as the document tag information ofthe inputted document image, and then imparts the information to thedocument image. In addition, the document tag information is registeredon the “document tag information” field 133 of the mark management table1213.

By applying the above-mentioned processing, it is possible toautomatically impart the document tag information to the inputteddocument image respectively. By using the information of each tableobtained here, the searching of the image can be performed according tothe following procedure.

First, when a user selects one of document tag information to be usedfor the searching, the mark management group Nos. corresponding to thedocument tag information can be specified from the mark management table1213. Additionally, the image IDs of the document image attached withthe mark management group No. and the pointer information to thedocument image data can be specified from the registration imagemanagement table 1212. The document image specified here becomes theimage correlated with the document tag information designated by theuser. By designating a plurality of document tag information, it ispossible to narrow down the image data to be searched.

When the document tag information with the maximum of the similaritycalculated by the similarity calculating means 1207 has the distance Lfrom the extracted mark image that is larger than the predeterminedthreshold value, it is judged that there is no registered document taginformation to be correlated with this mark image but new reference markis inputted. In this case, the mark image is displayed according to theinformation of the “position” field 134 and the “size” field 135 of themark management table 1213 and the “pointer to image data” field 122 ofthe registration image management table 1212, and then the user is askedto register the document tag information to be correlated with the newreference mark.

The document tag information inputted here is newly registered on the“reference tag information” field 141 of the reference tag informationmanagement table 1214. The image data of the reference mark inputtednewly is stored in the reference tag information storage means 1215 inorder to apply it to the succeeding researching, meanwhile the pointerinformation to the mark image data is registered on the “pointer toreference mark image” field 142 of the reference tag informationmanagement table 1214. In addition, the characteristics value of the newreference mark on the Moment Invariants is calculated and thenregistered on the “attribute values (M1 to M6)” field 143 of thereference tag information management table 1214.

As described above, a user executes the input of the new mark image andthe document tag information; thereby the new reference tag informationcan be registered.

Beside, in the above explanation, the reference tag informationcorrelated with the reference mark is the character string applied tothe reference mark as shown in FIG. 14 and FIG. 15( a), but thereference tag information needs not always to be the character string.That is to say, each reference mark can be correlated with any referencetag information in the reference tag management table 1214.

For example, instead of the reference tag information of theabove-mentioned character string, the thumbnail image of reference markis correlated with the reference mark as the reference tag informationrespectively. The thumbnail image is printed on a researching sheet. Byreading the thumbnail image of the researching sheet by a scanner, thedesired document image can be searched.

In order to specify the document tag information appointing page amongthe entire inputted images, the two-dimensional code is applied as shownin the explanatory diagrams in FIG. 13 and FIG. 16. However theone-dimensional code and so on can be used, too. There are other methodsfor specifying the document tag information appointing page than theabove, that is, a method that a specific mark is used instead of thetwo-dimensional code image, a method that a specific colored sheet isused, or a method that a specific formed sheet or a specific sized sheetis used. It is possible to obtain the same effect by those methods.

In addition, when the same document tag information is imparted to theentire inputted images, it is possible to arrange the document imageprocessor by defining that only the image to be inputted as the firstsheet is the image of the document tag information appointing page. Inthis case, since it has already been known that the image inputted asthe first sheet is the document tag information appointing page, itneeds not the processing for specifying the document tag appointing pageby the two-dimensional code image and so on. Therefore, it is possibleto simplify the processing as the whole.

It is needless to say that it is possible to extract the mark bysearching the entire pages of the paper document without using thetwo-dimensional code. At this time, it will happens that charactersincluded in the paper document, such as the “Confidential”, and etc. areextracted as a mark in addition to the mark attached by a user. In thiscase, the characters may be added to the mark management table 1213 asone of the mark.

The correlating between the mark image and the reference tag informationis performed by using the characteristics value on the Moment Invariantsin the above explanation, however it is possible to obtain the sameeffect by the correlating of the templates matching that compares therate of the black pixels matched by overlapping two images.

Besides, it is possible to correlate a plurality of the reference markswith a piece of reference tag information. This is carried out by thefollowing method; a plurality of the same reference tag information isregistered on the reference tag information management table 1214, andthen is correlated with the different reference mark respectively. Inthis case, after the paper document attached with different marks isinputted, the document images thus inputted is attached with the samedocument tag information.

Conversely, one reference mark can be correlated with a plurality ofreference tag information. This is carried out by the method that thedifferent reference tag information in the reference tag informationmanagement table 1214 is correlated with the same reference mark. Inthis case, after the paper document attached with one mark, the documentimage thus inputted is attached with a plurality of the document taginformation.

Embodiment 6

This embodiment describes the method for imparting the document taginformation to the document image by extracting the mark stamped at theblank part of the paper document to be registered. The followingsexpress the points different from that of the embodiment 5 withreference to FIG. 12.

The image inputting means 1201 obtains document images by electronicallyconverting a paper document inputted by a user, like the embodiment 5.As shown in FIG. 17( b), the document tag information of “Confidential”,“A-company”, and “year 99” is attached to the document images 31 and 32,while the document tag information of “Confidential” and “B-company” isattached to the document image 33. In order to perform processing, theblank part of each image is stamped with a mark correlated with thedocument tag information to be attached with.

The image data obtained here is stored in the image memory 1202temporarily. And after the data is compressed by the image datacompressing means 1203, it is stored in the image storage area 1211 ofthe storage means 1210. As the information about the stored image data,the necessary information is registered respectively in the “image ID”field 121′ and the “pointer to image data” field 122′ of theregistration image management table 1212′ as shown in FIG. 17( a), whichis the same as in the embodiment 5.

The image of the image memory 1202 is sent to the mark extracting means1205′ after the binarization by the image binarization means 1204. Inorder to extract the region of the mark image precisely, this embodimentuses a mark with frame as shown in FIG. 17( b) and performs theextracting of each mark by the mark extracting means 1205′ as follows.

Each black pixel of the binary image is labeled, and the size of thecircumscribing rectangle is calculated per black-pixel-connectedcomponent. At this time, the size of the circumscribing rectangle of theblack-pixel-connected component corresponding to the frame portion ofthe mark is large sufficiently comparing the each character sizeincluded in the inputted image, but does not get large extremely becausethe mark is stamped within the blank part of the document. By applyingthe characteristics, out of the black-pixel-connected componentsobtained by the labeling, only the region of which the circumscribingrectangle has the size between the specified two threshold values isextracted. That is to say, by extracting the region of theblack-pixel-connected component wherein the respective sizes of theheight and the width are larger than the specific threshold value (thatis considered as the minimum size of the blank (the height and thewidth)), and less than another threshold value (that is considered asthe maximum size of the blank), it is possible to extract the region ofeach mark image.

The number of marks extracted from the document images by the aboveprocessing is registered respectively on the “number of marks” field124′ of the registration image management table 1212′. Each extractedmark image is imparted with a mark ID respectively. The mark ID isregistered in the “mark ID” field 131′ of the mark management table1213′. In addition, the information about the image ID of the inputtedimage attached with the mark, the information about the position thatthe mark was attached, and the information about the mark size areregistered on the “image ID” field 132′, the “position” field 134′, andthe “size” field 135′ of the mark management table 1213′, respectively.

The embodiment of the invention is arranged so as to impart the documenttag information to the image attached with the mark only. Beside, whenan image is inputted between the image with the first mark and the otherimage with the next mark, if a user wants to manage it as a series ofthe document images included in the image with the first mark, they canbe managed by imparting the mark management group No. to those imageslike the embodiment 5.

Like the embodiment 5, the calculating means 120A (the characteristicsvalue calculating means 1206 and the similarity calculating means 1207)and the document tag information imparting means 1208 specify thedocument tag information correlated with the mark image according to thecharacteristics value of the Moment Invariants of the well-knowntechnology. And the specified document tag information is registered onthe “document tag information” field 133′ of the mark management table1213′.

If the above-mentioned processing is adopted, by the simple inputtingthat a mark is stamped on the blank of the paper document to beregistered, it is possible to imparting the document tag information bythe automatic searching. In this case, it is not necessary for thedocument tag information appointing page used in the embodiment 5, andthe only document to be registered is inputted. As described above, theregistration image management table 1212′ and the mark management table1213′ are configured simply more than that of the registration imagemanagement table 1212 and the mark management table 1213 in theembodiment 5.

It is needless to say that this embodiment can adopt the method forimparting the two-dimensional code to the page attached with a mark inorder to speed up the mark extracting.

In the invention of this embodiment, the mark stamped on the blank partof the side describing the content of the paper document is inputted.However, when a scanner and etc. can permit to scan both sides of thesheet, the input can be performed by stamping the mark on the backside.It can be also expected the same effect.

In addition, the mark has a frame, but the frame is not alwaysnecessary. In case of the mark without the frame, since it is consideredgenerally that the mark be configured by the black pixels contiguouscomponents of which size is larger than the characters included in thetext of the paper document, it is possible to apply the embodiment.

As mentioned above, first of all, since the invention is configured thatthe region of which the first average of the character size is largerthan the extracting criterion is extracted as the title region, it ispossible to extract a plurality of title regions from one documentimage. In addition, it is possible to perform the extracting judgment ona plurality of levels according to the extracting parameters on aplurality of levels. Thereby the title region can be determinedaccording to the characteristics of the document images inputted withthe extracting parameters on a plurality of levels. Since the trimmedmean method for calculating excluding both characters included in thespecific proportion of the larger side and those included in thespecific proportion of the smaller side is applied to the calculation ofthe second average of the character size and the calculation of thefirst average of the character size, it is possible to improve theprecision of the extracting.

Moreover, secondarily, the invention can impart the document taginformation to the inputted image automatically by inputting the markeddocument to the document image processor without using the keyboard orthe pointing device. By using the document tag information attached bythe processing, the document image can be searched. Therefore, it ispossible to manage and utilize the document image processor effectively.

1. A document image processor comprising: image inputting means forpreparing a document image by reading a paper document; region dividingmeans for dividing the document image into a plurality of regions; andtitle-region extracting means for calculating first averages as anaverage of character size for characters in each region divided by theregion dividing means, and then extracting title regions from therespective regions according to the first averages, wherein thetitle-region extracting means further comprises: means for calculating asecond average that is an average of character size for characterswithin all the regions; means for comparing the first averages andextracting criteria found by multiplying the second average byextracting parameters, the extracting parameters on a plurality oflevels calculated based on a value found by dividing a maximum of thefirst averages by the second average; and means for extracting theregions with the first average larger than the extracting criteria, asthe title region.
 2. A document image processor according to claim 1,wherein the title-region extracting means calculates the first averagesand the second average based on an average height of characters.
 3. Adocument image processor according to claim 1, wherein the title-regionextracting means calculates the first averages and the second averagebased on an average width of characters.
 4. A document image processoraccording to claim 1, wherein the title-region extracting meanscalculates the first averages and the second average based on an averagearea of characters.
 5. A document image processor according to claim 1,wherein the means for extracting the regions as the title region furtherextracts each level attribute indicating the level corresponding to eachextracted title region.
 6. A document image processor according to claim1, wherein the title-region extracting means adopts the trimmed meanmethod for discarding a specific proportion of the minimum and themaximum values and then computing the means of the remaining values, inorder to calculate the first averages and the second average ofcharacter size.
 7. A document image processor according to claim 6,wherein the characters of which character size are lower than thespecific portion are punctuation marks.
 8. A document image processoraccording to claim 1, further comprising correcting means for correctingcharacter strings of the extracted title regions.
 9. A document titleextracting method for a document image processor comprising: an imageinputting step of preparing a document image by reading a paperdocument; a dividing step of dividing a plurality of regions from thedocument image; a calculating step of calculating first averages as anaverage of character size for characters in each region; and atitle-region extracting step of extracting title regions from therespective regions according to the first averages, and wherein thecalculating step comprises a step for calculating a second average thatis an average of character size in all the regions, the title-regionextracting step comprises a step of comparing the first averages andextracting criteria found by multiplying the second average byextracting parameters, the extracting parameters on a plurality oflevels calculated based on a value found by dividing a maximum of thefirst averages by the second average; and a step of extracting theregions with the first average more than the extracting criteria, as thetitle region.
 10. A document title extracting method for a documentimage processor according to claim 9, in which the calculating stepcomprises a step of calculating the first averages and the secondaverage based on an average height of characters.
 11. A document titleextracting method for a document image processor according to claim 9,in which the calculating step comprises a step of calculating the firstaverages and the second average based on an average width of characters.12. A document title extracting method for a document image processoraccording to claim 9, in which the calculating step comprises a step ofcalculating the first averages and the second average based on anaverage area of characters.
 13. A document title extracting method for adocument image processor according to claim 9, in which the step ofextracting the regions as the title region further extracts each levelattribute indicating the level corresponding to each extracted titleregion.
 14. A document title extracting method of a document imageprocessor according to claim 9, further comprising the step of:correcting character strings of the extracted title regions.
 15. Acomputer readable medium storing a program for performing the steps of:dividing a document image prepared by reading a paper document into aplurality of regions; calculating first averages as an average ofcharacter size for characters within each region and a second averagethat is an average of character size in all the regions; comparing thefirst averages and extracting criteria found by multiplying the secondaverage by extracting parameters, the extracting parameters on aplurality of levels calculated based on a value found by dividing amaximum of the first averages by the second average; and extracting theregions with the first average more than the extracting criteria, as thetitle region.
 16. A document title extracting method for a documentimage processor comprising: an image inputting step of preparing adocument image by reading a paper; a dividing step of dividing aplurality of regions from the document image; a calculating step ofcalculating first averages as an average of character size forcharacters within each region; and a title-region extracting step ofextracting title regions from the respective regions according to thefirst averages, and wherein the calculating step comprises a step forcalculating a second average that is an average of character size in allthe regions, the title-region extracting step comprises a step ofcomparing the first averages and extracting criteria found bymultiplying the second average by extracting parameters, the extractingparameters on a plurality of levels calculated based on a value found bydividing a maximum of the first averages by the second average; and astep of extracting the regions with the first average larger than theextracting criteria, as the title region, and the first averages and thesecond average are calculated according to the trimmed mean method fordiscarding a specific proportion of the minimum and the maximum valuesand then computing the means of the remaining values.
 17. A documenttitle extracting method for a document image processor according toclaim 16, in which the calculating step comprises a step of calculatingthe first averages and the second average based on an average height ofcharacters.
 18. A document title extracting method for a document imageprocessor according to claim 16, in which the calculating step comprisesa step of calculating the first averages and the second average based onan average width of characters.
 19. A document title extracting methodfor a document image processor according to claim 16, in which thecalculating step comprises a step of calculating the first averages andthe second average based on an average area of characters.
 20. Adocument title extracting method of a document image processor accordingto claim 16, further comprising the step of: correcting characterstrings of the extracted title regions.
 21. A document title extractingmethod of a document image processor according to claim 16, wherein thecharacters of which character size are lower than the specific portionare punctuation marks.